This paper presents a novel top-down headdriven parsing algorithm for data-driven projective dependency analysis. This algorithm handles global structures, such as clause and coor...
We present a novel semi-supervised training algorithm for learning dependency parsers. By combining a supervised large margin loss with an unsupervised least squares loss, a discr...
In recent years, metric learning in the semisupervised setting has aroused a lot of research interests. One type of semi-supervised metric learning utilizes supervisory informatio...
We propose a top-down algorithm for extracting k-best lists from a parser. Our algorithm, TKA is a variant of the kbest A (KA) algorithm of Pauls and Klein (2009). In contrast to ...